14 citations · 20 across the 4 of their papers we have counts for
11 papers
Social network analytics for supervised fraud detection in insurance
María Óskarsdóttir, Waqas Ahmed, Katrien Antonio +4
Insurance fraud occurs when policyholders file claims that are exaggerated or based on intentional damages. This contribution develops a fraud detection strategy by extracting insi…
Instance-Dependent Cost-Sensitive Learning for Detecting Transfer Fraud
Sebastiaan Höppner, Bart Baesens, Wouter Verbeke +1
Card transaction fraud is a growing problem affecting card holders worldwide. Financial institutions increasingly rely upon data-driven methods for developing fraud detection syste…
Autoencoders for strategic decision support
Sam Verboven, Jeroen Berrevoets, Chris Wuytens +2
In the majority of executive domains, a notion of normality is involved in most strategic decisions. However, few data-driven tools that support strategic decision-making are avail…
robROSE: A robust approach for dealing with imbalanced data in fraud detection
Bart Baesens, Sebastiaan Höppner, Irene Ortner +1
A major challenge when trying to detect fraud is that the fraudulent activities form a minority class which make up a very small proportion of the data set. In most data sets, frau…
The Value of Big Data for Credit Scoring: Enhancing Financial Inclusion using Mobile Phone Data and Social Network Analytics
María Óskarsdóttir, Cristián Bravo, Carlos Sarraute +2
Credit scoring is without a doubt one of the oldest applications of analytics. In recent years, a multitude of sophisticated classification techniques have been developed to improv…
Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective
Tine Van Calster, Filip Van den Bossche, Bart Baesens +1
Choosing the technique that is the best at forecasting your data, is a problem that arises in any forecasting application. Decades of research have resulted into an enormous amount…